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Knowledge and Information Systems
Published in: Knowledge and Information Systems 3/2019

22-01-2019 | Regular Paper

An expected win rate-based real-time bidding strategy for branding campaigns on display advertising

Authors: Wen-Yueh Shih, Jiun-Long Huang

Published in: Knowledge and Information Systems | Issue 3/2019

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Abstract

For branding campaigns, the demand-side platforms (DSPs) in real-time bidding (RTB) usually need to win as many impressions as possible to inform most audiences about the product messages under constraints on budgets, campaign lifetimes and budget spending plans. In this paper, we propose a novel bidding strategy by introducing the concept of expected win rate. With the proposed expected win rate-based bidding strategy, the DSP can dynamically adjust the expected win rate for each incoming bid request based on factors such as the predicted number of bid requests in the near future, the remaining budget and the remaining lifetime of the campaign. The experimental results show that the proposed bidding strategy has a lower cost per thousand impressions and cost per clicks than existing pacing model-based bidding strategies for branding campaigns with the same budgets and budget spending plans.
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Appendix
Available only for authorised users
Footnotes
1
A display of an ad is called an impression.
 
2
Performing such actions is called a conversion.
 
3
The details of the real datasets, iPinYou and Tenmax, will be given in Sect. 5.1.
 
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Metadata
Title
An expected win rate-based real-time bidding strategy for branding campaigns on display advertising
Authors
Wen-Yueh Shih
Jiun-Long Huang
Publication date
22-01-2019
Publisher
Springer London
Published in
Knowledge and Information Systems / Issue 3/2019
Print ISSN: 0219-1377
Electronic ISSN: 0219-3116
DOI
https://doi.org/10.1007/s10115-019-01331-8

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